From the article: Here is a description of what they're trying to show in the graph at top:
From the article:
Epidemiologists usually pay far more attention to the trends indicated by epidemic curves — changes in the timing and slopes of their rise, flattening, and fall — rather than the case numbers that generated them. Disease detectives speak of “dirty data”, not pejoratively, but only to indicate awareness of so many factors why counts of infections, deaths, and other metrics are but shadows of varying blurriness on the wall of Plato’s cave in reflecting what is really happening.
Here is a description of what they're trying to show in the graph at top:
Our admittedly crude approximation to observe the effect of “opening up” is to stratify by political preferences: red, purple, and blue (Figure). Densely-populated areas, mostly “blue”, were seeded early by imported virus and hit hard. Urban transportation systems with crowded buses and trains likely facilitated transmission. Nevertheless, comprehensive lockdowns put them onto downslopes of their curves. But the epidemic continues to spread inexorably in rural areas, mostly “red” states, with more dispersed populations, different commuting means (car and pickup), and other features that may slow but not eliminate transmission.
From the article:
Here is a description of what they're trying to show in the graph at top: